| 基于自适应头狼的灰狼优化算法 |
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| 引用本文： | 郭阳,张涛,胡玉蝶,杜航.基于自适应头狼的灰狼优化算法[J].成都大学学报(自然科学版),2020(1):60-63,73. |
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| 作者姓名： | 郭阳 张涛 胡玉蝶 杜航 |
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| 作者单位： | ;1.长江大学信息与数学学院 |
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| 基金项目： | 湖北省教育厅科学技术研究(Q20171301)资助项目。 |
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| 摘 要： | 灰狼优化算法一种模拟灰狼捕食行为的元启发式优化算法.由于灰狼算法在种群迭代更新中始终靠近最优解,所以易陷入局部最优.提出了一种基于自适应头狼的灰狼优化算法,并在个体迭代更新中选择合适的头狼个数进行个体更新,这使得算法能够平衡开发和勘探能力.通过对20个基准函数优化问题的仿真实验表明,改进后的算法与原始灰狼优化算法相比,其全局搜索能力有显著提高.
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| 关 键 词： | 灰狼优化算法 局部最优 开发和勘探能力 头狼 |
Grey Wolf Optimizer Based on Adaptive Leader Wolf |
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| GUO Yang,ZHANG Tao,HU Yudie,DU Hang.Grey Wolf Optimizer Based on Adaptive Leader Wolf[J].Journal of Chengdu University (Natural Science),2020(1):60-63,73. |
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| Authors: | GUO Yang ZHANG Tao HU Yudie DU Hang |
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| Institution: | (School of Information and Mathematics,Yangtze University,Hubei 434023,China) |
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| Abstract: | Grey wolf optimizer is a meta-heuristic optimization algorithm to simulate the predatory behavior of grey wolf. Because the grey wolf optimizer is always close to the optimal solution in the iterative updating of population,it is easy to fall into the local optimum. This paper presents a grey wolf optimizer based on adaptive leader wolf. In the process of individual iterative updating,the appropriate number of leader wolves is selected for individual updating,which enables the algorithm to balance the exploitation and exploration capabilities. The simulation results of 20 benchmark function optimization problems show that the global search ability of the improved algorithm is significantly improved compared with that of the original grey wolf optimization algorithm. |
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| Keywords: | grey wolf optimization algorithm local optimization development and exploration ability leader wolf |
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